کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5523645 1546117 2017 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
ReviewSpectral analysis: A rapid tool for species detection in meat products
موضوعات مرتبط
علوم زیستی و بیوفناوری علوم کشاورزی و بیولوژیک دانش تغذیه
پیش نمایش صفحه اول مقاله
ReviewSpectral analysis: A rapid tool for species detection in meat products
چکیده انگلیسی


- Importance of meat species identification.
- Principle of spectral analytical techniques for meat species identification.
- Pre-processing techniques and multivariate analysis techniques.
- Differences in the spectra of various meat products with different species.
- Limitations of spectral analysis techniques.

BackgroundThe adulteration of meat products with undeclared or falsely declared animal species is a major concern all over the world. There are many analytical techniques for meat species identification but are time consuming and require highly skilled personnel. Thus, rapid and robust methods are needed for meat species identification. Spectral analysis techniques are rapid tools which can be used to classify and quantify different animal species in the meat products. Chemometric is data handling tool which can analyze the complex spectral data.Scope and approachThis review discusses major spectral analysis techniques suitable for meat species identification. The advantages of different data pre-processing and multivariate analysis techniques are also discussed. The spectral properties or fingerprints of the reference and analyte samples have also been summarized.Key findings and conclusionsVarious spectral analysis techniques have been used for meat species identification. Some studies revealed the importance of spectral analysis techniques for correct classification of different meat products according to the meat species present in them. However, there are some technical limitations of these methods, and to provide a robust solution to the meat industry, a comprehensive research should be done on these techniques with due consideration of all the limitations and process variables.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Trends in Food Science & Technology - Volume 62, April 2017, Pages 59-67
نویسندگان
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